A New Algorithm for Simultaneous Retrieval of Aerosols and Marine Parameters

Taddeo Ssenyonga,Dennis Muyimbwa,Knut Stamnes,Øyvind Frette,Jakob J Stamnes,Nicolausi Ssebiyonga,Børge Hamre

doi:10.3390/a15010004

Taddeo Ssenyonga, Dennis Muyimbwa + Show 5 more

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https://doi.org/10.3390/a15010004

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Abstract

We present an algorithm for simultaneous retrieval of aerosol and marine parameters in coastal waters. The algorithm is based on a radiative transfer forward model for a coupled atmosphere-ocean system, which is used to train a radial basis function neural network (RBF-NN) to obtain a fast and accurate method to compute radiances at the top of the atmosphere (TOA) for given aerosol and marine input parameters. The inverse modelling algorithm employs multidimensional unconstrained non-linear optimization to retrieve three marine parameters (concentrations of chlorophyll and mineral particles, as well as absorption by coloured dissolved organic matter (CDOM)), and two aerosol parameters (aerosol fine-mode fraction and aerosol volume fraction). We validated the retrieval algorithm using synthetic data and found it, for both low and high sun, to predict each of the five parameters accurately, both with and without white noise added to the top of the atmosphere (TOA) radiances. When varying the solar zenith angle (SZA) and retraining the RBF-NN without noise added to the TOA radiance, we found the algorithm to predict the CDOM absorption, chlorophyll concentration, mineral concentration, aerosol fine-mode fraction, and aerosol volume fraction with correlation coefficients greater than 0.72, 0.73, 0.93, 0.67, and 0.87, respectively, for 45∘≤ SZA ≤ 75∘. By adding white Gaussian noise to the TOA radiances with varying values of the signal-to-noise-ratio (SNR), we found the retrieval algorithm to predict CDOM absorption, chlorophyll concentration, mineral concentration, aerosol fine-mode fraction, and aerosol volume fraction well with correlation coefficients greater than 0.77, 0.75, 0.91, 0.81, and 0.86, respectively, for high sun and SNR ≥ 95.

Highlights

Introduction published maps and institutional affilAlgorithms for retrieval of atmospheric and marine parameters from measurements of back-scattered radiances at several wavelengths by instruments deployed on earthorbiting satellites have been developed over the past few decades.The earliest ocean color remote sensing algorithms were based on a two-step approach.First, an atmospheric correction was carried out to estimate the aerosol optical depth (AOD) at a near-infrared (NIR) channel (865 nm for Sea Wide Field of view (SeaWiFS)sensor), for which the ocean was assumed to be black (the NIR black-pixel approximation (NIR-BPA))
Gaussian noise added to the computed TOA radiances and (ii) low and high sun with different levels of white noise added to the computed TOA radiances
We have presented a new algorithm for simultaneous retrieval of two aerosol parameters and three marine parameters (CDOM absorption, chlorophyll concentration, and mineral concentration)

Summary

Introduction

Introduction published maps and institutional affilAlgorithms for retrieval of atmospheric and marine parameters from measurements of back-scattered radiances at several wavelengths by instruments deployed on earthorbiting satellites (ocean color data) have been developed over the past few decades.The earliest ocean color remote sensing algorithms were based on a two-step approach.First, an atmospheric correction was carried out to estimate the aerosol optical depth (AOD) at a near-infrared (NIR) channel (865 nm for Sea Wide Field of view (SeaWiFS)sensor), for which the ocean was assumed to be black (the NIR black-pixel approximation (NIR-BPA)). Algorithms for retrieval of atmospheric and marine parameters from measurements of back-scattered radiances at several wavelengths by instruments deployed on earthorbiting satellites (ocean color data) have been developed over the past few decades. The earliest ocean color remote sensing algorithms were based on a two-step approach. An atmospheric correction was carried out to estimate the aerosol optical depth (AOD) at a near-infrared (NIR) channel (865 nm for Sea Wide Field of view (SeaWiFS). AOD values for wavelengths in the visible range were obtained by extrapolation and used to generate water-leaving radiances [1,2,3,4,5]. The two-step algorithms employ regression or look-up table matching based on bio-optical models to estimate chlorophyll concentration from visible-channel water-leaving radiances.

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